The Essential Interview: Jacob Rosen, Surgical Robotics Pioneer

In the News

September 22, 2016

Joanne Pransky, associate editor of Industrial Robot, recently sat down with Jacob Rosen, a professor of medical robotics at the University of California, Los Angeles. The surgical robotics pioneer has developed systems for minimally invasive surgery, telesurgery, and exoskeletons.

Rosen got a B.S. degree in mechanical engineering, followed by an M.S. and Ph.D. in biomedical engineering, from Tel-Aviv University. He currently directs the Bionics Lab at UCLA’s Department of Mechanical and Aerospace Engineering.

In addition, Rosen is the director of surgical robotics engineering at the UCLA School of Medicine’s Center for Advanced Surgical and Interventional Technology. He has served as an expert witness and consultant on design, intellectual property, and malpractice.

Rosen has also filed eight patent applications and is co-founder of Applied Dexterity Inc., ExoSense Inc., and SPI Surgical Inc. Here, he talks about his research and how the process of getting federal approval affects the medical device market.

This interview is available free to Robotics Business Review readers until Oct. 21, 2016. Here’s a preview:

Pransky: How did you first come up with the concept of the Raven [telesurgery device]?

Rosen: When I started my postdoctoral studies at the University of Washington in 1997, along with my mentors Professors Blake Hannaford and Surgeon Mika Sinanan, we studied algorithms that could objectively assess surgical skills in minimally invasive surgery [MIS].

We used, in part, Hidden Markov Models, a method that was previously applied in speech recognition. This unexpected association of the modeling approach led me to the conclusion that MIS is essentially a spoken language with various words and different pronunciations used by all surgeons trying to tell the same story as they operate, regardless of their skill level.

The research challenge was to identify the words, pronunciation and the rules of grammar of surgery and use this framework to assess surgical skills objectively.

By analyzing hundreds of hours of surgical procedures, we managed to develop a model of specific surgical tasks for each skill level representing the training or expert levels.

A byproduct of this massive data collection of quantitative data that was recorded from instrumented surgical tools allowed us to gather the engineering specifications of a new surgical robot.